Fix typos

Xilinx · Jan 7, 2025 · 7371c8d · 7371c8d
1 parent 7b9b6fc
commit 7371c8d
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Showing 2 changed files with 7 additions and 7 deletions.
diff --git a/src/Dialect/ONNX/Transforms/Decompose.cpp b/src/Dialect/ONNX/Transforms/Decompose.cpp
@@ -856,7 +856,7 @@ class IndicesContiguousCounter {
 } // namespace
 
 // Decomposes ScatterNDs into a single Split and Concat.
-// We can always split an ScatterNDs by splitting the input tensor together with
+// We can always split ScatterNDs by splitting the input tensor together with
 // the indices and their updates belonging to that part of the input tensor,
 // performing the ScatterNDs on each split, and the concatenating the result.
 // Here, we handle certain ScatterNDs where after splitting them into three,
@@ -998,8 +998,8 @@ struct DecomposeScatterNDPattern : public OpRewritePattern<ONNXScatterNDOp> {
     // -- The expected index is calculated the following way:
     // --- The expected index is initialized with the first index in indices and
     //     then always incremented by one.
-    // --- The increment works like an manual addition, the least significant
-    //     digit/subindex gets incremented by one. If an digit overflows, it
+    // --- The increment works like a manual addition, the least significant
+    //     digit/subindex gets incremented by one. If a digit overflows, it
     //     gets reset to the first index and the addition carries to the next,
     //     more significant digit. The addition overflows, if the index for an
     //     axis is equal to the size of this axis in updates/indices. (By

diff --git a/test/mlir/onnx/onnx_decompose.mlir b/test/mlir/onnx/onnx_decompose.mlir
@@ -1148,21 +1148,21 @@ func.func @test_scatter_nd_dynamic(%data : tensor<*xf32>, %updates : tensor<1x1x
 // CHECK:        onnx.ScatterND
 
 // -----
-func.func @test_scatter_nd_mulit_dim_differ(%data : tensor<2x6x10x12xf32>, %updates : tensor<1x1x10x12xf32> ) -> tensor<2x6x10x12xf32> {
+func.func @test_scatter_nd_multi_dim_differ(%data : tensor<2x6x10x12xf32>, %updates : tensor<1x1x10x12xf32> ) -> tensor<2x6x10x12xf32> {
   %indices = onnx.Constant dense<[[[[0, 1, 0], [0, 1, 1], [0, 1, 2], [0, 1, 3], [0, 1, 4], [0, 1, 5], [0, 1, 6], [0, 1, 7], [0, 1, 8], [0, 1, 9]]]]> : tensor<1x1x10x3xi64>
   %0 = "onnx.ScatterND"(%data, %indices, %updates) {reduction = "none"} : (tensor<2x6x10x12xf32>, tensor<1x1x10x3xi64>, tensor<1x1x10x12xf32>) -> tensor<2x6x10x12xf32>
   onnx.Return %0 : tensor<2x6x10x12xf32>
 }
-// CHECK-LABEL:  func.func @test_scatter_nd_mulit_dim_differ
+// CHECK-LABEL:  func.func @test_scatter_nd_multi_dim_differ
 // CHECK:        onnx.ScatterND
 
 // -----
-func.func @test_scatter_nd_mulit_dim_differ_multi_shift(%data : tensor<2x6x10x12xf32>, %updates : tensor<1x1x10x12xf32> ) -> tensor<2x6x10x12xf32> {
+func.func @test_scatter_nd_multi_dim_differ_multi_shift(%data : tensor<2x6x10x12xf32>, %updates : tensor<1x1x10x12xf32> ) -> tensor<2x6x10x12xf32> {
   %indices = onnx.Constant dense<[[[[1, 1, 0], [1, 1, 1], [1, 1, 2], [1, 1, 3], [1, 1, 4], [1, 1, 5], [1, 1, 6], [1, 1, 7], [1, 1, 8], [1, 1, 9]]]]> : tensor<1x1x10x3xi64>
   %0 = "onnx.ScatterND"(%data, %indices, %updates) {reduction = "none"} : (tensor<2x6x10x12xf32>, tensor<1x1x10x3xi64>, tensor<1x1x10x12xf32>) -> tensor<2x6x10x12xf32>
   onnx.Return %0 : tensor<2x6x10x12xf32>
 }
-// CHECK-LABEL:  func.func @test_scatter_nd_mulit_dim_differ_multi_shift
+// CHECK-LABEL:  func.func @test_scatter_nd_multi_dim_differ_multi_shift
 // CHECK:        onnx.ScatterND
 
 // -----